Redefining the Role of Resection Weight Prediction in Reduction Mammaplasty and Breaking the "One-Scale-Fits-All" Paradigm.

BACKGROUND: Reduction mammaplasty is a highly effective procedure for treatment of symptomatic macromastia. Prediction of resection weight is important for the surgeon and the patient, but none of the current prediction models is widely accepted. Insurance carriers are arbitrarily using resection weight to determine medical necessity, despite published literature supporting that resection weight does not correlate with symptomatic relief. What is the most accurate method of predicting resection weight and what is its role in breast reduction surgery? METHODS: The authors conducted a retrospective review of patients who underwent reduction mammaplasty at a single institution from 2012 to 2017. A senior biostatistician performed multiple regression analysis to identify predictors of resection weight, and linear regression models were created to compare each of the established prediction scales to actual resected weight. Patient outcomes were evaluated. RESULTS: Three-hundred fourteen patients were included. A new prediction model was created. The Galveston scale performed the best (R = 0.73; p < 0.001), whereas the Schnur scale performed the worst (R = 0.43; p < 0.001). The Appel and Descamps scales had variable performance in different subcategories of body mass index and menopausal status (p < 0.01). Internal validation confirmed the Galveston scale's best predictive value; 38.6 percent and 28.9 percent of actual breast resection weights were below Schnur prediction and 500-g minimum, respectively, yet 97 percent of patients reported symptomatic improvement or relief. CONCLUSIONS: The authors recommend a patient-specific and surgeon-specific approach for prediction of resection weight in breast reduction. The Galveston scale fits the best for older patients with higher body mass indices and breasts requiring large resections. Medical necessity decisions should be based on patient symptoms, physical examination, and the physician's clinical judgment. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV.

Pain and Hand Function.

Pain is a unique somatosensory perception that can dramatically affect our ability to function. It is also a necessary perception, without which we would do irreparable damage to ourselves. In this article, the authors assess the impact of pain on function of the hand. Pain can be categorized into acute pain, chronic pain, and neuropathic pain. Hand function and objective measurements of hand function are analyzed as well as the impact of different types of pain on each of these areas.

Anatomy of the sternal origin of the pectoralis major: implications for subpectoral augmentation.

BACKGROUND: The pectoralis major typically is manipulated for implant coverage and pocket design in subpectoral breast augmentation. An understanding of its anatomy can guide successful creation of the implant pocket. OBJECTIVES: The authors evaluated the anatomy of the sternal origin of the pectoralis major to inform surgical planning, help establish a technique for subpectoral augmentation mammaplasty, and identify the most common locations of perforators. METHODS: The sternal origins of 24 pectoralis major muscles were dissected and examined in 15 female cadavers to determine the structure and width of the pectoralis major sternal origin and its relationship to the locations of internal mammary perforators. RESULTS: The average width of the sternal origin of the pectoralis major was 7.1 mm (range, 3 mm-1.8 cm). This width decreased slightly from the second rib to the second intercostal space and then increased progressively in the caudal direction toward the fifth rib. The sternal origin terminated an average of 5.4 mm (range, 1-16 mm) from the midline, with the greatest distance at the fifth rib and large variability throughout. A row of perforators from the internal mammary artery traversed the subpectoral space an average of 2.7 cm from the midline (range, 1-3.7 cm). CONCLUSIONS: The sternal origin of the pectoralis major was thin and highly variable, suggesting that its partial release for implant medialization during subpectoral augmentation is unsafe.

Lymph node involvement in immunohistochemistry-based molecular classifications of breast cancer.

BACKGROUND: Prognosis and treatment options differ for each molecular subtype of breast cancer, but risk of regional lymph node (LN) metastasis for each subtype has not been well studied. Since LN status is the most important predictor for prognosis, the aim of this study is to investigate the propensity for LN metastasis in each of the five breast cancer molecular subtypes. METHODS: Under an institutional review board-approved protocol, we retrospectively reviewed the charts of all pathologically confirmed breast cancer cases from January 2004 to June 2012. Five subtypes were defined as luminal A (hormone receptor positive, Ki-67 low), luminal B (hormone receptor positive, Ki-67 high), luminal human epidermal growth factor receptor 2 (HER2), HER2-enriched (hormone receptor negative), and triple negative (TN). RESULTS: A total of 375 patients with complete data were classified by subtype: 95 (25.3%) luminal A, 120 (32%) luminal B, 69 (18.4%) luminal HER2, 26 (6.9%) HER2-enriched, and 65 (17.3%) TN. On univariate analysis, age (<50), higher tumor grade, HER2+ status, tumor size, and molecular subtype were significant for LN positivity. Molecular subtype correlated strongly with tumor size (χ(2); P = 0.0004); therefore, multivariable logistic regression did not identify molecular subtype as an independent variable to predict LN positivity. CONCLUSIONS: Luminal A tumors have the lowest risk of LN metastasis, whereas luminal HER2 subtype has the highest risk of LN metastasis. Immunohistochemical-based molecular classification can be readily performed and knowledge of the factors that affect LN status may help with treatment decisions.